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The Subgroup Imperative: Chest Radiograph Classifier Generalization Gaps in Patient, Setting, and Pathology Subgroups
23
Zitationen
7
Autoren
2023
Jahr
Abstract
Performance of deep learning chest radiograph classifiers was subject to patient, setting, and pathology factors, demonstrating that subgroup analysis is necessary to inform implementation and monitor ongoing performance to ensure optimal quality, safety, and equity.<b>Keywords:</b> Conventional Radiography, Thorax, Ethics, Supervised Learning, Convolutional Neural Network (CNN), Machine Learning Algorithms <i>Supplemental material is available for this article.</i> © RSNA, 2023See also the commentary by Huisman and Hannink in this issue.
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